Phase 3

Surveillance is crucial to provide a broad picture of the
extent, location and condition of semi-natural habitats across the
UK. This knowledge is necessary to acquire sufficient knowledge
about specific species and habitats of conservation concern to
enable their protection and the meeting of legislative obligations
such as the EC Habitats Directive.

This project constitutes Phase 3 of a wider project to address
the role of EO data in habitat monitoring and surveillance needs in
the UK, and comprised a number of tasks:

further technical and applications development, in an upland
environment (the focus of
previous work was essentially in lowland landscapes and
habitats);

developing inputs for a business case – identifying users and
uses, setting out the
rationale for adoption and rollout of EO habitat mapping across the
UK and
demonstrating cost-effectiveness of the approach through the
example of Habitats
Directive (Article 17) reporting of Annex I habitats;

providing coordination and information exchange with others in
the EO and conservation
sector.

Review and scoping of Earth Observation potential

JNCC and DEFRA have been working together on a project called
Making Earth Observation Work for UK Biodiversity (MEOW), which has
so far included two phases. The aim of Phase 1 of this project was
to review recent activity, and report on the potential of using
Earth Observation (EO) techniques for biodiversity surveillance of
terrestrial and freshwater habitats. During the review and
consultations it became clear that current habitat classification
systems are not necessarily suitable for describing habitats using
EO methods alone. A “one-size-fits-all” approach will not
deliver information on any habitat measure for the full range of
higher priority habitats. There is also a wide variation in
the use, knowledge and capacity of organisations to adopt the range
of EO techniques currently available or under development.
Overall, surveillance and monitoring needs are going to
require a range of techniques tailored to the particular habitats,
the features of interest, and size of the area under
surveillance.

The review concluded that many of the EO based techniques are
effective for filling gaps in mapping the location and extent of a
range of habitats including those with dynamic environments.
They were also highly cost-effective in comparison to field
survey methods and manual EO interpretation, over significant
areas. EO techniques would also contribute to effective
targeting of field survey for habitats that will continue to
require field survey for their identification. The report
summarises the current use of such techniques by UK country
conservation agencies and made a range of recommendations for
future actions to promote best practice and facilitate uptake of
the most promising techniques. The project also proposed the
Crick
Framework, grouping habitats based on the ability of EO and
ancillary data to accurately map them.

Developing new methods and the Crick Framework approach

The main objective of Phase 2 of MEOW was to undertake a pilot
project within Norfolk to test the Crick Framework approach for
applied use of EO for operational habitat surveillance and
monitoring. The detailed content of the Crick Framework was
also independently peer reviewed.

The pilot used a range of EO techniques, including data from
Landsat and DMC (Disaster Monitoring Constellation - 30m pixel
size) through to SPOT (Satellite Pour l'Observation de la Terre -
10m), RapidEye (6.5m) and GeoEye-1 (1.65m) satellites, as well as
colour infra-red air photography (0.5m). It also incorporated
data captured using a Remotely Piloted Aerial System (RPAS), which
allows for repeatable, high-resolution multi-spectral data, aerial
photography and detailed surface model data to be captured at time
critical points.

Using these EO techniques, the pilot tested the
transferability of existing methods within Norfolk, examining which
BAP Priority and Annex 1 habitats can be found and where the
approaches are repeatable. These methods work by creating a
rulebase that combines various data. Three rulebases were
generated in this work; two of them start from attributes within
Ordnance Survey data and a third was created specifically for the
coastal areas. Flow diagrams describing these rulebases are
downloadable below.

Identification of habitats from EO Imagery requires two sorts
of knowledge:

Ecological knowledge about the habitats of interest, including
how they appear from above, and their characteristics in the
different spectral bands available.

Understanding and ability to manipulate the digital remote
sensing data within a system, to find the communities and to
separate them out from the rest of the landscape.

The findings from the pilot study were used to produce a
detailed Crick
Framework spreadsheet that provides, for each Biodiversity
Action Plan (BAP) Priority and Annex 1 habitat, a detailed
habitat description and the relevant EO methods and ancillary data
requirements. The Phase 2 final report can be downloaded above.
Phase 3 is currently underway, looking at mapping upland
habitats.

Using EO to Assess Habitat Condition

Maintaining and enhancing the ecological condition of
semi-natural habitats and avoiding their loss or deterioration, is
vital to maintaining ecosystem services. Monitoring the ecological
condition of habitats is a time consuming process using standard
field techniques. The pilot tested the use of EO techniques
to measure four habitat conditions: vegetation productivity, single
species stands of negative and positive indicators, wetness/dryness
and freshwater metrics.

Table 1 summarises the measurements used for each of the four
habitat conditions and their associated pilot results. These
findings are an initial analysis into the potential of EO as a
monitoring tool for habitat condition and more detail can be found
in the Phase 2 report. More work will be necessary to develop
these into robust techniques.

Table 1. Habitat condition, measurement and
result from Norfolk pilot.

Habitat Condition

Measurement

Pilot result

Vegetation productivity

Normalised Difference Vegetation Index
(NDVI)

Productivity maps were produced at a range of scales that
allowed visualisation and quantification of the nutrient balance
within and around sites.

Single species stands of negative and positive
indicators

Purple moor-grass (Molinia caerulea);

Nettles (Urtica dioica);

Gorse scrub (Ulex sp);

Birch scrub (Betula sp);

Himalayan balsam (Impatiens glandulifera).

The extent of a range of competitive and invasive plant
species that can be damaging to sites was classified successfully
with a range of types of EO.

Wetness/dryness

Normalised Difference Wetness Index (NDWI);

Modified Normalised Difference Wetness Index
(MNDWI).

Use of a NDWI allowed mires to be classified into a number of
wetness categories. Use of a MNDWI was found to have the
potential to identify wet and

dry woodlands.

Freshwater metrics

Chlorophyll-A concentrations;

Total Suspended Solids (TSS).

A preliminary investigation showed Rapid Eye imagery measured
and mapped the eutrophic nature and TSS of water bodies.